{"id":"W2145292907","doi":"10.1109/ccece.2004.1347640","title":"Constraint-based routing across multi-domain optical WDM networks","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Provisioning; Wavelength-division multiplexing; Routing (electronic design automation); Distributed computing; Computer network; Constraint (computer-aided design); Quality of service; Path (computing); Scheme (mathematics); Domain (mathematical analysis); Wavelength; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001762765,0.0006599642,0.0007311922,0.0003654757,0.0009116529,0.001005028,0.001359322,0.001183933,0.001605099],"category_scores_gemma":[0.003977713,0.0004519336,0.000429718,0.0007406228,0.0009984662,0.001338849,0.0008807552,0.000793911,0.00009231209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001382076,"about_ca_system_score_gemma":0.001458589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006714859,"about_ca_topic_score_gemma":0.006198019,"domain_scores_codex":[0.9990789,0.0004138776,0.00003849023,0.0001178818,0.0002235455,0.0001273939],"domain_scores_gemma":[0.9974158,0.0019146,0.0002886922,0.0001121134,0.0001379641,0.0001308918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005239768,0.00002304389,0.0001796147,0.0000297311,0.0000138511,0.0000789679,0.00001873323,0.9896354,0.000884234,0.005666964,0.0001314381,0.003285585],"study_design_scores_gemma":[0.00001445418,0.00001624093,0.00005240596,0.000001615574,0.000003461001,0.00001270854,0.000006347144,0.9975492,0.00039696,0.00179018,0.0001538107,0.00000272412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2067946,0.0003424853,0.7877959,0.0004830416,0.00004915422,0.0002429675,0.0001631857,0.0002230055,0.00390567],"genre_scores_gemma":[0.8817102,0.0002453112,0.1164828,0.00005392911,0.00001799133,0.0001706444,0.00009006879,0.00003749573,0.001191585],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006714859,"threshold_uncertainty_score":0.01335156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257756935943595,"score_gpt":0.250742153897262,"score_spread":0.238164584537826,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}